Simulating the performance of a class-based weighted fair queueing system
Pages 2901 - 2908
Abstract
Class Based Weighted Fair Queueing (CBWFQ) is a very important router discipline that allows different types of Internet Protocol (IP) traffic like voice, video, and best effort data to receive the required quality of service measures they individually need. CBWFQ dynamically allocates the available bandwidth to each traffic class based on the class's weight. This discipline is playing a vital role as IP brings these traffic classes together in a truly converged network. Under stress and in extreme emergencies, it is critical to be able to determine how the CBWFQ discipline will perform. In this paper, we present and discuss the critical role simulation has played in our development of performance analysis tools for the CBWFQ discipline.
References
[1]
Altman, E., K. Avrachenkov, and U. Ayesta. 2006. A Survey on Discriminatory Processor Sharing. Queueing Systems 53: 53--63.
[2]
Cao, J., W. S. Cleveland, D. Lin, and D. X. Sun. 2002. Internet Traffic Tends Toward Poisson and Independent as the Load Increases. Nonlinear Estimation and Classification. Editors: C. Holmes, D. Denison, M. Hansen, B. Yu, and B. Mallick, Springer, New York, NY. http://cm.bellabs.com/who/dong/papers/lrd2poisson.pdf.
[3]
Cidon, I. and M. Sidi. 1990. Recursive Computation of Steady-State Probabilities in Priority Queueing Systems. Operations Research Letters, Vol. 9, No. 4, pp. 249--256.
[4]
Cisco Systems, IOS Quality of Service Solutions Configuration Guide, Release 12.2 (Congestion Management Overview). http://www.cisco.com/en/US/proucts/sw/iosswrel/ps1835/products_configuration_guide_chapter09186a00800b75a9.html.
[5]
Cohen, J. W. 1969. The Single Server Queue. North-Holland Publishing Company, New York, NY.
[6]
Fischer, M. J., and D. M. B. Masi. 2005. Voice Packet Arrival Models and Their Effect on Packet Performance. Applied Telecommunications Symposium, San Diego, CA.
[7]
Gross, D. and C. M. Harris. 1998. Fundamentals of Queueing Theory. Third Edition, John Wiley, New York, NY.
[8]
Kleinrock, L. and H. Levy. 1988. The Analysis of Random Polling Systems. Operations Research 36 (5): 716--732.
[9]
Knepley, J. E. and M. J. Fischer. 1977. A Numerical Solution for some Computational Problems Occurring in Queueing Theory. TIMS Studies in the Management Sciences, Vol. 7: 271--285.
[10]
Lee, T. 1997. A Closed Form Solution for the Asymmetric Random Polling System with Correlated Levy Input Process. Mathematics of Operations Research 22 (2): 432--457.
[11]
Masi, D. M. B., M. J. Fischer, and D. A. Garbin. 2007a. Modeling the Performance of Class Based Weighted Fair Queueing with OPNET and Custom Simulators. OPNETWORK Conference, Washington, DC.
[12]
Masi, D. M. B., M. J. Fischer, and D. A. Garbin. 2007b. Modeling the Performance of Low Latency Queueing for Emergency Telecommunications. Winter Simulation Conference, Washington, DC.
[13]
Miller, D. R. 1981. Computation of Steady-State Probabilities for M/M/1 Priority Queues. Operations Research 28 (5).
[14]
Morse, P. M. 1958. Queue, Inventories and Maintenance. Wiley, New York, NY.
[15]
Newman, D., G. Chagnot, and J. Perser. 2001. Networking the Telecom Industry, Light Reading. Detailed Methodology, Section 3-Test Procedures. www.lightreading.com/document.asp?doc_id=3972.
[16]
Parekh, A. K. and R. G. Gallager. 1993. "A Generalized Processor Sharing Approach to Flow Control in Integrated Services Networks: The Single-node Case." IEEE/ACM Transactions on Networking 1 (3): 344--357.
[17]
Semeria, C. 2001. "Supporting Differentiated Service Class: Queue Scheduling Disciplines." Juniper White Paper. http://www.juniper.net/soltions/literture/white_papers/200020.pdf.
[18]
Takagi, H. 1986. "Analysis of Polling Systems." The MIT Press, Cambridge, MA.
[19]
Takagi, H. 1988. Queueing Analysis of Polling Models." ACM Computing Surveys 20 (1): 5--28.
[20]
Thompson, K., G. J. Miller, and R. Wilder. 1997. Wide Area Internet Traffic Patterns and Characteristics. IEEE Network.
- Simulating the performance of a class-based weighted fair queueing system
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Published In
December 2008
3189 pages
ISBN:9781424427086
- Editors:
- Scott Mason,
- Ray Hill,
- Lars Mönch,
- Oliver Rose,
- General Chair:
- Thomas Jefferson,
- Program Chairs:
- John W. Fowler,
- Ricki G. Ingalls
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- IIE: Institute of Industrial Engineers
- INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
- ASA: American Statistical Association
- IEEE/SMC: Institute of Electrical and Electronics Engineers: Systems, Man, and Cybernetics Society
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- NIST: National Institute of Standards and Technology
- (SCS): The Society for Modeling and Simulation International
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Winter Simulation Conference
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Published: 07 December 2008
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WSC '08 Paper Acceptance Rate 249 of 304 submissions, 82%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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